{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T00:58:55Z","timestamp":1781225935056,"version":"3.54.1"},"reference-count":47,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,4,20]],"date-time":"2026-04-20T00:00:00Z","timestamp":1776643200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T00:00:00Z","timestamp":1781222400000},"content-version":"vor","delay-in-days":53,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/501100003662","name":"Korea Evaluation Institute of Industrial Technology","doi-asserted-by":"publisher","award":["No. 1415181754"],"award-info":[{"award-number":["No. 1415181754"]}],"id":[{"id":"10.13039\/501100003662","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["RS-2024-00336583"],"award-info":[{"award-number":["RS-2024-00336583"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"DOI":"10.1038\/s41598-026-48640-x","type":"journal-article","created":{"date-parts":[[2026,4,20]],"date-time":"2026-04-20T15:56:31Z","timestamp":1776700591000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Spectrometer-free time-division multiplexed NIR time-of-flight vision system for visually similar material recognition"],"prefix":"10.1038","volume":"16","author":[{"given":"Tae-In","family":"Jeong","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jae-Young","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eunji","family":"Choi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"San","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sehyeon","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Munki","family":"Song","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junho","family":"Lee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexander","family":"Gliserin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert A.","family":"Taylor","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seungchul","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,4,20]]},"reference":[{"key":"48640_CR1","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1109\/MIM.2014.6825388","volume":"17","author":"S Shirmohammadi","year":"2014","unstructured":"Shirmohammadi, S. & Ferrero, A. Camera as the instrument: The rising trend of vision based measurement. IEEE Instrum. Meas. Mag. 17, 41\u201347 (2014).","journal-title":"IEEE Instrum. Meas. Mag."},{"key":"48640_CR2","unstructured":"BinYan, L., YanBo, W., ZhiHong, C., JiaYu, L. & JunQin, L. In Chin Autom Congr,. 7277\u20137281 (IEEE)."},{"key":"48640_CR3","doi-asserted-by":"publisher","DOI":"10.3390\/technologies12020015","volume":"12","author":"N Manakitsa","year":"2024","unstructured":"Manakitsa, N., Maraslidis, G. S., Moysis, L. & Fragulis, G. F. A review of machine learning and deep learning for object detection, semantic segmentation, and human action recognition in machine and robotic vision. Technologies (Basel) 12, 15 (2024).","journal-title":"Technologies (Basel)"},{"key":"48640_CR4","doi-asserted-by":"publisher","DOI":"10.3390\/s16030335","volume":"16","author":"L P\u00e9rez","year":"2016","unstructured":"P\u00e9rez, L., Rodr\u00edguez, \u00cd., Rodr\u00edguez, N., Usamentiaga, R. & Garc\u00eda, D. F. Robot guidance using machine vision techniques in industrial environments: A comparative review. Sensors (Basel) 16, 335 (2016).","journal-title":"Sensors (Basel)"},{"key":"48640_CR5","doi-asserted-by":"publisher","DOI":"10.3390\/robotics11060139","volume":"11","author":"MT Shahria","year":"2022","unstructured":"Shahria, M. T. et al. A comprehensive review of vision-based robotic applications: Current state, components, approaches, barriers, and potential solutions. Robotics 11, 139 (2022).","journal-title":"Robotics"},{"key":"48640_CR6","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1007\/s11633-024-1517-1","volume":"22","author":"X Xiao","year":"2025","unstructured":"Xiao, X., Jiang, Y. & Wang, Y. Key technologies for machine vision for picking robots: Review and benchmarking. Mach. Intell. Res. 22, 2\u201316 (2025).","journal-title":"Mach. Intell. Res."},{"key":"48640_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/OJIM.2024.3493875","volume":"4","author":"D Preethichandra","year":"2024","unstructured":"Preethichandra, D., Piyathilaka, L. & Izhar, U. Review on robotic systems for environmental monitoring. IEEE Open J. Instrum. Meas. 4, 1\u201317 (2024).","journal-title":"IEEE Open J. Instrum. Meas."},{"key":"48640_CR8","unstructured":"Nguyen, R. M., Prasad, D. K. & Brown, M. S. In European Conference on Computer Vision, 186\u2013201 (Springer)."},{"key":"48640_CR9","doi-asserted-by":"publisher","first-page":"4716","DOI":"10.1109\/TITS.2023.3248483","volume":"24","author":"Y Li","year":"2023","unstructured":"Li, Y., Moreau, J. & Ibanez-Guzman, J. Emergent visual sensors for autonomous vehicles. IEEE Trans. Intell. Transp. Syst. 24, 4716\u20134737 (2023).","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"48640_CR10","unstructured":"Bell, S., Upchurch, P., Snavely, N. & Bala, K. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 3479\u20133487."},{"key":"48640_CR11","doi-asserted-by":"publisher","first-page":"1981","DOI":"10.1109\/TPAMI.2019.2907850","volume":"42","author":"G Schwartz","year":"2019","unstructured":"Schwartz, G. & Nishino, K. Recognizing material properties from images. IEEE Trans. Pattern Anal. Mach. Intell. 42, 1981\u20131995 (2019).","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"48640_CR12","doi-asserted-by":"publisher","DOI":"10.3390\/jimaging10030073","volume":"10","author":"L Wunsch","year":"2024","unstructured":"Wunsch, L., Tenorio, C. G., Anding, K., Golomoz, A. & Notni, G. Data fusion of rgb and depth data with image enhancement. J. Imaging 10, 73 (2024).","journal-title":"J. Imaging"},{"key":"48640_CR13","doi-asserted-by":"publisher","DOI":"10.1002\/lpor.71005","volume":"20","author":"Z Zheng","year":"2026","unstructured":"Zheng, Z. et al. Exploiting scattering-based point spread functions for snapshot 5D and modality-switchable lensless imaging. Laser Photonics Rev. 20, e71005 (2026).","journal-title":"Laser Photonics Rev."},{"key":"48640_CR14","doi-asserted-by":"publisher","DOI":"10.1063\/5.0120465","author":"N Baek","year":"2022","unstructured":"Baek, N., Lee, Y., Kim, T., Jung, J. & Lee, S. A. Lensless polarization camera for single-shot full-Stokes imaging. APL Photonics https:\/\/doi.org\/10.1063\/5.0120465 (2022).","journal-title":"APL Photonics"},{"key":"48640_CR15","doi-asserted-by":"publisher","first-page":"2789","DOI":"10.1007\/s12008-023-01320-w","volume":"17","author":"AG Satav","year":"2023","unstructured":"Satav, A. G., Kubade, S., Amrutkar, C., Arya, G. & Pawar, A. A state-of-the-art review on robotics in waste sorting: Scope and challenges. Int. J. Interact. Design Manuf. (IJIDeM) 17, 2789\u20132806 (2023).","journal-title":"Int. J. Interact. Design Manuf. (IJIDeM)"},{"key":"48640_CR16","doi-asserted-by":"publisher","DOI":"10.3390\/s25123668","volume":"25","author":"X Zhang","year":"2025","unstructured":"Zhang, X., Wang, H. & Dong, H. A survey of deep learning-driven 3D object detection: Sensor modalities, technical architectures, and applications. Sensors 25, 3668 (2025).","journal-title":"Sensors"},{"key":"48640_CR17","doi-asserted-by":"crossref","unstructured":"Ward, I. R., Laga, H. & Bennamoun, M. In RGB-D Image Analysis and Processing 169\u2013201 (Springer, 2019).","DOI":"10.1007\/978-3-030-28603-3_8"},{"key":"48640_CR18","doi-asserted-by":"publisher","first-page":"1998218","DOI":"10.1155\/2023\/1998218","volume":"2023","author":"B Zhu","year":"2023","unstructured":"Zhu, B. et al. Surrounding object material detection and identification method for robots based on ultrasonic echo signals. Appl. Bionics Biomech. 2023, 1998218 (2023).","journal-title":"Appl. Bionics Biomech."},{"key":"48640_CR19","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1255\/jnirs.747","volume":"15","author":"N Heigl","year":"2007","unstructured":"Heigl, N. et al. Near infrared spectroscopy for polymer research, quality control and reaction monitoring. J. Near Infrared Spectrosc. 15, 269\u2013282 (2007).","journal-title":"J. Near Infrared Spectrosc."},{"key":"48640_CR20","doi-asserted-by":"publisher","DOI":"10.3390\/app142311049","author":"H Song","year":"2024","unstructured":"Song, H. et al. Short-wave infrared (SWIR) imaging for robust material classification: Overcoming limitations of visible spectrum data. Appl. Sci. (Basel) (2076-3417) https:\/\/doi.org\/10.3390\/app142311049 (2024).","journal-title":"Appl. Sci. (Basel) (2076-3417)"},{"key":"48640_CR21","doi-asserted-by":"publisher","first-page":"9228","DOI":"10.1364\/AO.501582","volume":"62","author":"A Manakkakudy","year":"2023","unstructured":"Manakkakudy, A., De Iacovo, A., Maiorana, E., Mitri, F. & Colace, L. Material classification based on a SWIR discrete spectroscopy approach. Appl. Opt. 62, 9228\u20139237 (2023).","journal-title":"Appl. Opt."},{"key":"48640_CR22","unstructured":"Hansen, M. P. & Malchow, D. S. In Thermosense Xxx. 94\u2013104 (SPIE)."},{"key":"48640_CR23","doi-asserted-by":"crossref","unstructured":"Hussein, M. E., Spinoulas, L., Xiong, F. & Abd-Almageed, W. In 2018 IEEE International Workshop on Information Forensics and Security (WIFS), 1\u20138 (IEEE).","DOI":"10.1109\/WIFS.2018.8630773"},{"key":"48640_CR24","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2024.3480227","author":"H Liu","year":"2024","unstructured":"Liu, H., Yang, J., Fang, H., Ji, T. & Cai, Z. MSI-RGB dual-source multiscale fusion-based solid waste object detection. IEEE Trans. Instrum. Meas. https:\/\/doi.org\/10.1109\/TIM.2024.3480227 (2024).","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"48640_CR25","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1016\/j.wasman.2017.10.015","volume":"72","author":"Y Zheng","year":"2018","unstructured":"Zheng, Y., Bai, J., Xu, J., Li, X. & Zhang, Y. A discrimination model in waste plastics sorting using NIR hyperspectral imaging system. Waste Manag. 72, 87\u201398 (2018).","journal-title":"Waste Manag."},{"key":"48640_CR26","doi-asserted-by":"publisher","first-page":"802","DOI":"10.1039\/D3EM00324H","volume":"26","author":"G Bragato","year":"2024","unstructured":"Bragato, G., Piccolo, G., Sattier, G. & Sada, C. Identification of spectral responses of different plastic materials by means of multispectral imaging. Environ. Sci. Process. Impacts 26, 802\u2013813 (2024).","journal-title":"Environ. Sci. Process. Impacts"},{"key":"48640_CR27","doi-asserted-by":"publisher","first-page":"593","DOI":"10.1016\/j.psep.2023.09.052","volume":"179","author":"MK Singh","year":"2023","unstructured":"Singh, M. K., Hait, S. & Thakur, A. Hyperspectral imaging-based classification of post-consumer thermoplastics for plastics recycling using artificial neural network. Process. Saf. Environ. Prot. 179, 593\u2013602 (2023).","journal-title":"Process. Saf. Environ. Prot."},{"key":"48640_CR28","doi-asserted-by":"publisher","first-page":"4149","DOI":"10.1109\/JLT.2024.3521919","volume":"43","author":"A Song","year":"2024","unstructured":"Song, A. et al. Impact of phase error on coherent Lidar: Analysis and validation. J. Lightwave Technol. 43, 4149\u20134155 (2024).","journal-title":"J. Lightwave Technol."},{"key":"48640_CR29","doi-asserted-by":"publisher","first-page":"101101","DOI":"10.1063\/5.0079234","volume":"120","author":"Y Li","year":"2022","unstructured":"Li, Y. et al. Hyperspectral imaging through scattering layers with incoherent light. Appl. Phys. Lett. 120, 101101 (2022).","journal-title":"Appl. Phys. Lett."},{"key":"48640_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2021.110450","volume":"189","author":"Z Shang","year":"2022","unstructured":"Shang, Z. et al. Measurement of gear tooth profiles using incoherent line structured light. Measurement 189, 110450 (2022).","journal-title":"Measurement"},{"key":"48640_CR31","doi-asserted-by":"publisher","first-page":"543","DOI":"10.1080\/10739149.2022.2047061","volume":"50","author":"F Akkoyun","year":"2022","unstructured":"Akkoyun, F. Inexpensive multispectral imaging device. Instrum. Sci. Technol. 50, 543\u2013559 (2022).","journal-title":"Instrum. Sci. Technol."},{"key":"48640_CR32","unstructured":"Gr\u00f6nwall, C. et al. In Electro-Optical Remote Sensing, Photonic Technologies, and Applications VII; and Military Applications in Hyperspectral Imaging and High Spatial Resolution Sensing, 32\u201346 (SPIE)."},{"key":"48640_CR33","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-021-90587-8","volume":"11","author":"R Tobin","year":"2021","unstructured":"Tobin, R., Halimi, A., McCarthy, A., Soan, P. J. & Buller, G. S. Robust real-time 3D imaging of moving scenes through atmospheric obscurant using single-photon LiDAR. Sci. Rep. 11, 11236 (2021).","journal-title":"Sci. Rep."},{"key":"48640_CR34","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1016\/j.isprsjprs.2020.05.022","volume":"166","author":"S Pan","year":"2020","unstructured":"Pan, S. et al. Land-cover classification of multispectral LiDAR data using CNN with optimized hyper-parameters. ISPRS J. Photogramm. Remote Sens. 166, 241\u2013254 (2020).","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"48640_CR35","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1080\/07038992.2016.1196584","volume":"42","author":"C Hopkinson","year":"2016","unstructured":"Hopkinson, C., Chasmer, L., Gynan, C., Mahoney, C. & Sitar, M. Multisensor and multispectral LiDAR characterization and classification of a forest environment. Can. J. Remote Sens. 42, 501\u2013520 (2016).","journal-title":"Can. J. Remote Sens."},{"key":"48640_CR36","doi-asserted-by":"publisher","first-page":"5443","DOI":"10.1364\/OE.477499","volume":"31","author":"V Sivaprakasam","year":"2023","unstructured":"Sivaprakasam, V. et al. Multi-spectral SWIR lidar for imaging and spectral discrimination through partial obscurations. Opt. Express 31, 5443\u20135457 (2023).","journal-title":"Opt. Express"},{"key":"48640_CR37","doi-asserted-by":"publisher","first-page":"7057","DOI":"10.3390\/s100707057","volume":"10","author":"Y Chen","year":"2010","unstructured":"Chen, Y. et al. Two-channel hyperspectral LiDAR with a supercontinuum laser source. Sensors-Basel 10, 7057\u20137066 (2010).","journal-title":"Sensors-Basel"},{"key":"48640_CR38","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1016\/j.isprsjprs.2019.01.014","volume":"149","author":"S Song","year":"2019","unstructured":"Song, S. et al. A new waveform decomposition method for multispectral LiDAR. ISPRS J. Photogramm. Remote Sens. 149, 40\u201349 (2019).","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"48640_CR39","unstructured":"Fredell, M., Rahmlow Jr, T., Cote, W., Mann, R. & Johnson Jr, R. In Free-Space Laser Communications XXXII, 323\u2013330 (SPIE)."},{"key":"48640_CR40","unstructured":"Benton, D. M. In Electro-Optical and Infrared Systems: Technology and Applications XXI, 58\u201367 (SPIE)."},{"key":"48640_CR41","doi-asserted-by":"publisher","first-page":"11445","DOI":"10.1038\/s41598-024-62342-2","volume":"14","author":"S Kim","year":"2024","unstructured":"Kim, S. et al. Time division multiplexing based multi-spectral semantic camera for LiDAR applications. Sci. Rep-Uk 14, 11445 (2024).","journal-title":"Sci. Rep-Uk"},{"key":"48640_CR42","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1109\/MIM.2021.9436102","volume":"24","author":"H Al Osman","year":"2021","unstructured":"Al Osman, H. & Shirmohammadi, S. Machine learning in measurement Part 2: Uncertainty quantification. IEEE Instrum. Meas. Mag. 24, 23\u201327 (2021).","journal-title":"IEEE Instrum. Meas. Mag."},{"key":"48640_CR43","doi-asserted-by":"publisher","first-page":"1737","DOI":"10.1109\/50.9991","volume":"6","author":"RS Tucker","year":"2002","unstructured":"Tucker, R. S., Eisenstein, G. & Korotky, S. K. Optical time-division multiplexing for very high bit-rate transmission. J. Lightwave Technol. 6, 1737\u20131749 (2002).","journal-title":"J. Lightwave Technol."},{"key":"48640_CR44","unstructured":"Hamilton, S., Robinson, B., Moores, J., Hakimi, F. & Schulz, P. In Optical Fiber Communication Conference. WO3 (Optica Publishing Group)."},{"key":"48640_CR45","doi-asserted-by":"publisher","first-page":"1666","DOI":"10.1109\/PROC.1970.7988","volume":"58","author":"TS Kinsel","year":"2005","unstructured":"Kinsel, T. S. Wide-band optical communication systems: Part I\u2014Time division multiplexing. Proc. IEEE 58, 1666\u20131683 (2005).","journal-title":"Proc. IEEE"},{"key":"48640_CR46","unstructured":"Krizhevsky, A., Sutskever, I. & Hinton, G. E. Imagenet classification with deep convolutional neural networks. In Advances in Neural Information Processing Systems, Vol. 25 (2012)."},{"key":"48640_CR47","unstructured":"Long, J., Shelhamer, E. & Darrell, T. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 3431\u20133440."}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-48640-x","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-48640-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-48640-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T00:12:03Z","timestamp":1781223123000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-48640-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,20]]},"references-count":47,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["48640"],"URL":"https:\/\/doi.org\/10.1038\/s41598-026-48640-x","relation":{},"ISSN":["2045-2322"],"issn-type":[{"value":"2045-2322","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,20]]},"assertion":[{"value":"14 February 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 April 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 April 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"Human involvement in this study was limited to non-medical measurements for system evaluation. No medical or clinical procedures were involved. Formal approval from a named institutional or licensing committee was not required for this work. Informed consent was obtained from the participant prior to the measurements and for publication of the images.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}}],"article-number":"18314"}}